Focused on applying imaging biomarkers and radiomics to cancer discovery, our efforts center on advancing precision imaging in personalized medicine to ultimately improve outcomes for cancer patients.
Over the past year, we have fostered new collaborations with leading imaging research groups at Cardiff (Wales, UK), the Champalimaud Foundation (Lisbon, Portugal), and the New York University School of Medicine (NY, USA). We have also forged new partnerships with other excellent research institutes including the German Cancer Research Center – Deutsches Krebsforschungszentrum, DKFZ (Heidelberg, Germany), and the Dresden University Hospital (Dresden, Germany).
We are thrilled to announce that two European projects, TANGERINE, and ODELIA, have recently received funding. These projects will provide a unique opportunity to establish valuable networks of collaborators with multidisciplinary and complementary expertise. This will accelerate the development and application of novel AI-tools in cancer research, ultimately leading to advancements in clinical practice. We are honored to be working alongside such esteemed partners, and we look forward to the groundbreaking discoveries that will come from these collaborations.
Continuing our collaboration with VHIO’s Research Unit for Molecular Therapy of Cancer (UITM) – CaixaResearch led by Elena Garralda, and thanks to the support received through an AstraZeneca Partners of Choice Award, we are working on the PREDICT study to develop predictive biomarkers of response to immune checkpoint inhibitors by combining radiomics, genomics and the molecular characterization of the tumor microenvironment by multiplexed assays.
We also participate in the EU-funded Cancer Core Europe Consortium’s DART project – Building Data Rich Clinical Trials, which is led by VHIO’s Elena Garralda. Aimed at optimizing clinical trial design, we are providing support to achieve image protocol standardization and integration of novel imaging biomarkers.
We are also exploring new diffusion-weighted MRI protocols to evaluate biological-specific metrics regarding tissue cellularity and cell size in the liver. We envision that the metrics derived from this new assay will have important applications as non-invasive biomarkers in cancer. Francesco Grussu, a Post-Doctoral Fellow of our group, has been granted a LaCaixa Retaining post-doctoral fellowship this year to pursue this research.
Thanks to the support received from the Instituto de Salud Carlos III – ISCIII (Institute of Health Carlos III), and the Prostate Cancer Foundation’s (PCF) Young Investigator Award, our group coordinates a multi-center prospective study of whole-body diffusion-weighted MRI as a response biomarker of bone metastasis in prostate cancer patients. This study was expanded to include breast cancer patients thanks to funding received from La Marató de TV3 (PreciMet study). We are pleased to announce that patient recruitment for our trial was completed by the final quarter of 2022. We are eagerly anticipating the announcement of results from this ambitious project.
We have established several interdisciplinary partnerships with various VHIO groups to work together on translational research projects. Our ethos of team science is key to optimizing imaging and accelerating translational research against cancer. Focused on applying imaging biomarkers and radiomics to cancer discovery, our efforts center on advancing precision imaging in personalized medicine to ultimately improve outcomes for cancer patients.
- Develop and optimize pipelines for AI-models of data integration with particular focus on medical imaging and the integration process of explainable models.
- Provide expertise in engineering and bioinformatics for the development and clinical qualification of imaging biomarkers for precision oncology to improve outcomes for cancer patients.
- Use functional imaging to optimize drug development in clinical trials.
- Integrate radiomics with genomics in translational studies to achieve a deeper understanding of tumor evolution and mechanisms of resistance to anti-cancer therapies.
- Develop and implement computational models for advanced image processing.
Figure: DW microstructural MRI metrics provide biological-specific metrics that offer sensitivity to tumorigenic processes in the liver such as metastases.
Group Leader
Raquel Perez-Lopez
Post-Doctoral Fellows
Caterina Tozzi
Francesco Grussu
PhD Students
Alonso García
Marta Ligero
Olivia Prior
Athanasios Grigoriou
Anna Voronova
Computer Scientist
Camilo Monreal
Adrià Marcos
Laboratory Technician
Daniel Navarro
Research Fellow
Luz María Atlagich
Students
Maria Balaguer,
Ella Fokkinga
Bente Gielen
Nikolaos Staikoglou
Carlos Macarro Pérez
Data curator
Christina Zatse
Most relevant scientific publications
- Ghaffari Laleh N, Ligero M, Perez-Lopez R, Kather JN. Facts and Hopes on the Use of Artificial Intelligence for Predictive Immunotherapy Biomarkers in Cancer. Clin Cancer Res. 2023 Jan 17;29(2):316-323.
- Ligero, M., Hernando, J., Delgado, E. et al. Radiomics and outcome prediction to antiangiogenic treatment in advanced gastroenteropancreatic neuroendocrine tumours: findings from the phase II TALENT trial. BJC Rep 1, 9 (2023).
- Ligero M, Simó M, Carpio C, Iacoboni G, Balaguer-Montero M, Navarro V, Sánchez-Salinas MA, Bobillo S, Marín-Niebla A, Iraola-Truchuelo J, Abrisqueta P, Sala-Llonch R, Bosch F, Perez-Lopez R, Barba P. PET-based radiomics signature can predict durable responses to CAR T-cell therapy in patients with large B-cell lymphoma. EJHaem. 2023 Sep 11;4(4):1081-1088.
- Ramlee S, Hulse D, Bernatowicz K, Pérez-López R, Sala E, Aloj L. Radiomic Signatures Associated with CD8+ Tumour-Infiltrating Lymphocytes: A Systematic Review and Quality Assessment Study. Cancers (Basel). 2022 Jul 27;14(15):3656.
- Grussu F, Bernatowicz K, Casanova-Salas I, Castro N, Nuciforo P, Mateo J, Barba I, Perez-Lopez R. Diffusion MRI signal cumulants and hepatocyte microstructure at fixed diffusion time: Insights from simulations, 9.4T imaging, and histology. Magn Reson Med. 2022 Jul;88(1):365-379.
- Elez E, Ros J, Fernández J, Villacampa G, Moreno-Cárdenas AB, Arenillas C, Bernatowicz K, Comas R, Li S, Kodack DP, Fasani R, Garcia A, Gonzalo-Ruiz J, Piris-Gimenez A, Nuciforo P, Kerr G, Intini R, Montagna A, Germani MM, Randon G, Vivancos A, Smits R, Graus D, Perez-Lopez R, Cremolini C, Lonardi S, Pietrantonio F, Dienstmann R, Tabernero J, Toledo RA. RNF43 mutations predict response to anti-BRAF/EGFR combinatory therapies in BRAFV600E metastatic colorectal cancer. Nat Med. 2022 Oct;28(10):2162-2170.
- Pons-Escoda A, Garcia-Ruiz A, Naval-Baudin P, Grussu F, Fernandez JJS, Simo AC, Sarro NV, Fernandez-Coello A, Bruna J, Cos M, Perez-Lopez R, Majos C. Voxel-level analysis of normalized DSC-PWI time-intensity curves: a potential generalizable approach and its proof of concept in discriminating glioblastoma and metastasis. Eur Radiol. 2022 Jun;32(6):3705-3715.
- Grussu, F; et al. Diffusion MRI signal cumulants and hepatocyte microstructure at fixed diffusion time: insights from simulations, 9.4T imaging and histology. Magnetic Resonance in Medicine. 2022. doi: 10.1002/mrm.29174 (en prensa).
- Pons-Escoda A, García-Ruiz A, Naval-Baudin P, Grussu F, Fernández JJS, Simóo AC, Sarróo NV, Fernández-Coello A, Bruna J, Cos M, Pérez-López R, Majos C. Voxel-level analysis of normalized DSC-PWI time-intensity curves: a potential generalizable approach and its proof of concept in discriminating glioblastoma and metastasis. Eur Radiol. 2022 Feb 1. DOI: 10.1007/s00330-021-08498-1.
- Bernatowicz, K., Grussu, F., Ligero, M. et al. Robust imaging habitat computation using voxel-wise radiomics features. Sci Rep 11, 20133 (2021). doi: 10.1038/s41598-021-99701-2.
- Ligero M, García-Ruiz A, Viaplana C, Villacampa G, Raciti MV, Landa J, Matos I, Martín-Liberal J, Ochoa-de-Olza M, Hierro C, Mateo J, González M, Morales-Barrera R, Suárez C, Rodón J, Elez E, Braña I, Muñoz-Couselo E, Oaknin A, Fasani R, Nuciforo P, Gil D, Rubio-Pérez C, Seoane J, Felip E, Escobar M, Tabernero J, Carles J, Dienstmann R, Garralda E, Pérez-López R. A CT-based Radiomics Signature Is Associated with Response to Immune Checkpoint Inhibitors in Advanced Solid Tumors. Radiology. 2021 Apr;299(1):109-119. doi: 10.1148/radiol.2021200928.
- García-Ruiz A, Naval-Baudin P, Ligero M, Pons-Escoda A, Bruna J, Plans G, Calvo N, Cos M, Majós C, Pérez-López R. Precise enhancement quantification in post-operative MRI as an indicator of residual tumor impact is associated with survival in patients with glioblastoma. Sci Rep. 2021 Jan 12;11(1):695. doi: 10.1038/s41598-020-79829-3.
- Ligero M, Jordi-Ollero O, Bernatowicz K, García-Ruiz A, Delgado-Muñoz E, Leiva D, Mast R, Suárez C, Sala-Llonch R, Calvo N, Escobar M, Navarro-Martín A, Villacampa G, Dienstmann R, Pérez-López R. Minimizing acquisition-related radiomics variability by image resampling and batch effect correction to allow for large-scale data analysis. Eur Radiol. 2021 Mar;31(3):1460-1470. doi: 10.1007/s00330-020-07174-0.
- Zunder SM, Pérez-López R, de Kok BM, Raciti MV, van Pelt GW, Dienstmann R, García-Ruiz A, Meijer CA, Gelderblom H, Tollenaar RA, Nuciforo P, Wasser MN, Mesker WE. Correlation of the tumour-stroma ratio with diffusion weighted MRI in rectal cancer. Eur J Radiol. 2020 Dec;133:109345. doi: 10.1016/j.ejrad.2020.109345.
- Matos I, Martín-Liberal J, García-Ruiz A, Hierro C, Ochoa de Olza M, Viaplana C, Azaro A, Vieito M, Braña I, Mur G, Ros J, Mateos J, Villacampa G, Berché R, Oliveira M, Alsina M, Elez E, Oaknin A, Muñoz-Couselo E, Carles J, Felip E, Rodón J, Tabernero J, Dienstmann R, Pérez-López R, Garralda E. Capturing Hyperprogressive Disease with Immune-Checkpoint Inhibitors Using RECIST 1.1 Criteria. Clin Cancer Res. 2020 Apr 15;26(8):1846-1855. doi: 10.1158/1078-0432.CCR-19-2226.
Main R&D projects
- IMPRINT: Imaging Markers for Personalized Response in ImmunoTherapy. Department of Research and Universities of Catalonia. 2024-2026.
- TANGERINE: Artificial-intelligence-based end-to-end prediction of cancer immunotherapy response. TRANSCAN Program (Spanish Association against Cancer and Instituto de Salud Carlos III). 2023-2025.
- ODELIA: An Open Consortium for Decentralized Medical Artificial Intelligence. H2020 Program (European Commission). 2023-2028.
- MARION: Multimodal biomarkers for precise management of metastatic prostate cancer. Proyectos de colaboración público-privada (Industry Ministry Spanish Government). 2023-2025.
- PRECISE: Deciphering colon cancer heterogeneity with machine learning and precision imaging. Instituto de Salud Carlos III. 2022-2025.
- Tumoral senescence induced by anti-cancer therapies constitutes a novel prognostic biomarker and a therapeutic target. Fundación Científica Asociación Española Contra el Cáncer-Proyectos Coordinados. 2021-2026.
- CCE-DART: Building Data Rich Clinical Horizon 2020 Program – European Commission. VHIO. 2021-2026.
- Unraveling the tumor immunophenotype with deep-learning based FERO Foundation Research Fellowship.
- PREdICT: Personalized REsponse Imaging biomarker for Cancer Therapy. CRIS Cancer Foundation Research Talent Program, AstraZeneca PoC Award
- PrecIMet: precision imaging for bone metastases. Fundació La Marató.
- Immune-Image: Specific Imaging of Immune Cell Dynamics Using Novel Tracer Horizon 2020-Innovative Medicine Initiatives (IMI2-Call4; 831514).
- Validación clínica de la resonancia de cuerpo completo con difusión en pacientes con cáncer de próstata resistente a la castración y metástasis óseas. Instituto de Salud Carlos III-Investigación en Salud (PI18/01395).
Personnel grants
- Beatriu de Pinós post-doctoral fellowship: “Advancing Magnetic Resonance Imaging against liver cancer”. Fellow: Francesco Grussu. 2022-2024.
- Fundación La Caixa, INPhINIT Retaining Fellowship. PhD in Biomedical Engineering (Universidad Politecnica de Cataluña). Predoctoral researcher: Olivia Prior.2021-2024.
- PERIS-Predoctoral fellowship. PhD in Biomedical Engineering (University of Barcelona). Predoctoral researcher: Marta Ligero. 2021-2024.
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