Outputs
OPTIMA in a nutshell
You want to find out more about OPTIMA? Get short but concise information in our Factsheet – OPTIMA at a glance, presenting all key information, or read in more detail in our overview documents – prepared for the expert audience (Overview – Principles and Key Objectives) and in lay language, addressed to patients (Overview – for patients) or to learn more about the use of Artificial Intelligence (AI) within OPTIMA (AI Explainer).
Video Library
OPTIMA oncology project introduction
OPTIMA (Optimal Treatment for Patients with Solid Tumours in Europe Through Artificial intelligence) is a € 21.3 million public-private research programme that will seek to use AI to improve care for patients with prostate, breast and lung cancer.
The Public – Patient Advisory Board
The ultimate goal of OPTIMA is to find better, more personalised treatment options for patients and to ensure that they have a good quality of life. Listen to four members of the OPTIMA Public/Patient Advisory Board on their involvement in patient advocacy organisations, their cancer journeys and their hopes for future patients.
Conchi Biurrun, Spanish Breast Cancer Federation of Associations
Conchi Biurrun from the Spanish Breast Cancer Federation of Associations and member of the OPTIMA Public/Patient Advisory Board speaks about her journey as a patient with breast cancer, her involvement in the OPTIMA project and her hopes that this project will lead to better, more personalised treatment options and a better quality of life for patients.
Erik Briers, European Prostate Cancer Coalition
Erik Briers from the European Prostate Cancer Coalition and member of the OPTIMA Patient and Public Advisory Board talks about his cancer journey and how a project such as OPTIMA can help other patients to receive optimal treatment with the help of real-life evidence and guidelines.
Seamus Cotter, Irish Lung Cancer Community
Listen to Seamus Cotter from the Irish Lung Cancer Community and member of the OPTIMA Patient and Public Advisory Board on his experiences with clinical trials and the importance of giving clear information on specific treatments to patients for an informed decision.
Marjo Forsblom, Lung Cancer Europe
Marjo Forsblom from Lung Cancer Europe was a member of the OPTIMA Public/Patient Advisory Board. In this video, she explained how OPTIMA will be putting health data to good use and aims to to develop a tool that knows what’s best for a patient in a specific situation. Sadly, she passed away in October 2023. With her familiy’s blessing, we decided to keep her video here. She will be very much missed by her OPTIMA friends and colleagues.
Nadia Harbeck, LMU
Learning from real-world well-protected data to find the best therapies
Listen to Dr. Nadia Harbeck, head of of the Breast Center LMU University Hospital in Munich, explaining about big data, real-world evidence & Artificial Intelligence within the context of breast cancer treatment and research as part of the OPTIMA project.
Torsten Blum, Helios
The importance to share clinical data for a most valuable OPTIMA platform- Torsten Blum
Dr. Torsten Gerriet Blum, senior physician and pneumologist at Helios Klinikum, is explaining about the importance of data sharing, big data, real-world evidence & Artificial Intelligence within the context of lung cancer treatment and research as part of the OPTIMA project.
Michael Bussmann, Helmholtz
Using Artificial Intelligence to transform data into knowledge
Dr. Michael Bussmann, founding manager of CASUS (Center for Advanced Systems Understanding) is leading the Work Package on Artificial Intelligence knowledge base implementation within OPTIMA. In this video, learn more about how AI can bring added value within the context of oncology care as part of the OPTIMA project.
Nicolas Mottet, EAU
Improving guidelines through real-world data for better treatment
Prof. Dr. Nicolas Mottet is Head of the Urology Department at Centre Hospitalier Universitaire de Saint-Etienne and involved as a Chairman at EAU. He explains how to improve guidelines through real-world data for better treatment in the context of prostate cancer treatment and research as part of the OPTIMA project.
Andreas Kremer & Bertrand De Meulder
Making the OPTIMA platform most useful for all stakeholders
Dr. Andreas Kremer & Dr. Bertrand De Meulder are leading the task of the analysis of the platform requirements, implementation and evaluation. In this video, you can learn more about the plans for the OPTIMA platform and about the role of artificial intelligence within the context of healthcare as part of the OPTIMA project.
Dr. Pippa Powell
The involvement of the Patient and Public Advisory Board of OPTIMA
Dr. Pippa Powell, Manager at the European Lung Foundation, is creating the link between patients, and patient organisations and research stresses in this video the importance of patient involvement within the OPTIMA project.
Peter-Paul Willemse, OPTIMA
Sharing big data and real-world evidence to solve clinical questions
Dr. Peter-Paul Willemse is Assistant Professor and Medical Doctor at the Department of Urological Oncology at UMC Utrecht. Within OPTIMA, he represents the clinical community treating prostate cancer patients and explains how sharing big data and real-world evidence may help to solve clinical questions as part of the OPTIMA project.
Prof. Daniel Prieto Alhambra
Big Data in the context of healthcare
Daniel Prieto Alhambra is professor of Pharmaco- and Device Epidemiology leading the workpackage on (non) interventional study data and real-world data gathering within OPTIMA. In this video, he discusses the role of big data within the context of healthcare as part of the OPTIMA project.
Monique Roobol
Transforming guidelines into electronic decision making tools for individual patients
Monique Roobol is Professor of Decision-Making in Urology and is explaining here about the OPTIMA project and why it is important that the project is translating clinical guidelines into electronic decision support tools.
James N’Dow and Hagen Krüger
Joining forces in a PPP to find better treatments for cancer patients
Prof. Dr. James N’ Dow, Academic Coordinator and EAU Adjunct Secretary General and Dr. Hagen Krüger, Senior Medical Director at Pfizer coordinating the OPTIMA project together. Here, they give an overview on the project and are talking about the importance of collaboration between public and private partners under IMI.
Public Deliverables
Below, please find links to all finalised public deliverables of the OPTIMA consortium:
Publications
Barclay Nicola L., Pineda Moncusí Marta, Jödicke Annika M., Prieto-Alhambra Daniel, Raventós Berta, Newby Danielle, Delmestri Antonella, Man Wai Yi, Chen Xihang, Català Marti. The impact of the UK COVID-19 lockdown on the screening, diagnostics and incidence of breast, colorectal, lung and prostate cancer in the UK: a population-based cohort study. Frontiers in Oncology. 2024, vol. 14, DOI=10.3389/fonc.2024.1370862
Barclay NL, Burkard T, Burn E, Delmestri A, Miquel Dominguez A, Golozar A, Guarner-Argente C, Avilés-Jurado FX, Man WY, Roselló Serrano À, Rosen AW, Tan EH, Tietzova I, Prieto Alhambra D, Newby D; OPTIMA Consortium. The Impact of the COVID-19 Pandemic on Incidence and Short-Term Survival for Common Solid Tumours in the United Kingdom: A Cohort Analysis. Clin Epidemiol. 2024 Jun 11;16:417-429. doi: 10.2147/CLEP.S463160. PMID: 38882578; PMCID: PMC11179647.
E. Lavrova et al., “UR-CarA-Net: A Cascaded Framework With Uncertainty Regularization for Automated Segmentation of Carotid Arteries on Black Blood MR Images,” in IEEE Access, vol. 11, pp. 26637-26651, 2023, doi: 10.1109/ACCESS.2023.3258408.
Salahuddin, Z.; Chen, Y.; Zhong, X.; Woodruff, H.C.; Rad, N.M.; Mali, S.A.; Lambin, P. From Head and Neck Tumour and Lymph Node Segmentation to Survival Prediction on PET/CT: An End-to-End Framework Featuring Uncertainty, Fairness, and Multi-Region Multi-Modal Radiomics. Cancers 2023, 15, 1932. https://doi.org/10.3390/cancers15071932
N’Dow J., Smith E.J., Polychronopoulos K., Cannon A., Roobol M. J., Auweter S., Thomas M., Kremer A., De Meulder B., Dellamonica D., Prieto-Alhambra D., Asiimwe A., Bussmann M., Xiang J., Torremante P., Keller S., Kube F., Krüger H., OPTIMA Consortium. (2022) OPTIMA: Improve care for patients with prostate, breast, and lung cancer through artificial intelligence ESMO #917P e-Posters – ESMO Congress 2022 (ctimeetingtech.com)
Refaee, T., Bondue, B., Van Simaeys, G., Wu, G., Yan, C., Woodruff, H. C., Goldman, S., & Lambin, P. (2022). A Handcrafted Radiomics-Based Model for the Diagnosis of Usual Interstitial Pneumonia in Patients with Idiopathic Pulmonary Fibrosis. J Pers Med, 12(3). https://doi.org/10.3390/jpm12030373
Li, R., Sharma, V., Thangamani, S., & Yakimovich, A. (2022). Open-Source Biomedical Image Analysis Models: A Meta-Analysis and Continuous Survey. Front Bioinform, 2, 912809. https://doi.org/10.3389/fbinf.2022.912809
Halilaj I, Oberije C, Chatterjee A, van Wijk Y, Rad NM, Galganebanduge P, Lavrova E, Primakov S, Widaatalla Y, Wind A, Lambin P. Open Source Repository and Online Calculator of Prediction Models for Diagnosis and Prognosis in Oncology. Biomedicines. 2022 Oct 23;10(11):2679. doi: 10.3390/biomedicines10112679. PMID: 36359199; PMCID: PMC9687260.
Refaee, T.; Salahuddin, Z.; Widaatalla, Y.; Primakov, S.; Woodruff, H.C.; Hustinx, R.; Mottaghy, F.M.; Ibrahim, A.; Lambin, P. CT Reconstruction Kernels and the Effect of Pre- and Post-Processing on the Reproducibility of Handcrafted Radiomic Features. J. Pers. Med. 2022, 12, 553. https://doi.org/10.3390/jpm12040553
Refaee, T., Salahuddin, Z., Frix, A.-N., Yan, C., Wu, G., Woodruff, H. C., Gietema, H., Meunier, P., Louis, R., Guiot, J., & Lambin, P. (2022). Diagnosis of Idiopathic Pulmonary Fibrosis in High-Resolution Computed Tomography Scans Using a Combination of Handcrafted Radiomics and Deep Learning [Original Research]. Frontiers in Medicine, 9. https://doi.org/10.3389/fmed.2022.915243
Keek SA, Beuque M, Primakov S, Woodruff HC, Chatterjee A, van Timmeren JE, Vallières M, Hendriks LEL, Kraft J, Andratschke N, Braunstein SE, Morin O, Lambin P. Predicting Adverse Radiation Effects in Brain Tumors After Stereotactic Radiotherapy With Deep Learning and Handcrafted Radiomics. Front Oncol. 2022 Jul 13;12:920393. doi:10.3389/fonc.2022.920393. PMID: 35912214; PMCID: PMC9326101.
Ibrahim A, Barufaldi B, Refaee T, Silva Filho TM, Acciavatti RJ, Salahuddin Z, Hustinx R, Mottaghy FM, Maidment ADA, Lambin P. MaasPenn Radiomics Reproducibility Score: A Novel Quantitative Measure for Evaluating the Reproducibility of CT-Based Handcrafted Radiomic Features. Cancers (Basel). 2022 Mar 22;14(7):1599. doi:10.3390/cancers14071599. PMID: 35406372; PMCID: PMC8997100.
Griesinger F, Curigliano G, Thomas M, Subbiah V, Baik CS, Tan DSW, Lee DH, Misch D, Garralda E, Kim DW, van der Wekken AJ, Gainor JF, Paz-Ares L, Liu SV, Kalemkerian GP, Houvras Y, Bowles DW, Mansfield AS, Lin JJ, Smoljanovic V, Rahman A, Kong S, Zalutskaya A, Louie-Gao M, Boral AL, Mazières J. Safety and efficacy of pralsetinib in RET fusion-positive non-small-cell lung cancer including as first-line therapy: update from the ARROW trial. Ann Oncol. 2022 Nov;33(11):1168-1178. doi:10.1016/j.annonc.2022.08.002. Epub 2022 Aug 13. PMID: 35973665.
